Robotics Controls Engineer

Join Us in Building the Future of Home Robotics

At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time.

We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we’d love to hear from you.

In building robots for the home, we are tackling a true grand challenge in robotics: dexterous and safe mobile manipulation in unstructured environments. To make this possible, we are building across the entire robotics stack. We’re training state-of-the-art AI models that leverage our large-scale, high-quality, real-world data collection system. At the same time, we’re building a new kind of consumer hardware product, which will be deployed into homes and delivering real value for real customers.

As an early member of a small, cross-functional team, you’ll play a key role in pushing both our technology and product forward: advancing the frontier of embodied AI, and soon giving countless hours back to our customers so they can spend more time on the things they value most.

As a Robotics Controls Engineer, you will design, implement, and test the control software that ensures our robot’s actions are safe, natural, responsive, and smooth. In this role, you will work closely with our ML team to translate novel manipulation capabilities into reliable and trustworthy whole-body behaviors. You’ll also work closely with our hardware team to characterize system dynamics, tune feedback controllers, and identify opportunities to improve performance in future robot designs.

• Develop whole-body control algorithms to produce stable, smooth, and precise motion for redundant mobile manipulators

• Implement and tune real-time feedback control systems to achieve reliable control performance on edge compute hardware running latency-sensitive workloads

• Develop observers, state estimators, and/or sensor fusion algorithms to support adaptive, robust, and contact-rich robot interactions

• Perform system  and design new calibration processes to characterize robot hardware

• Support hardware team in developing future robot platforms by identifying, quantifying, and communicating key aspects of robot hardware design impacting control performance

• Help build software and systems for robot performance evaluation, monitoring, and logging

• Deep understanding of rigid body kinematics, dynamics, and spatial math

• Strong mathematical background in linear and nonlinear systems and control theory

• Experience with model-based whole-body control methods for mobile manipulation

• Hands‑on experience developing and testing control systems on robotics hardware

• Experience writing production‑quality software in Python or C++

• Experience with kinematics/dynamics/simulation libraries such as Pinocchio, Mujoco, Isaac

• MS or PhD in robotics, control theory, or related field

• Experience with RL and/or imitation learning methods for robot manipulation or locomotion

• Experience with hybrid motion-force control methods such as operational-space control / inverse dynamics / computed-torque control

• 2 years of experience working with robot hardware in academic or production environment

At Sunday Robotics, we’re building technology shaped by real people — curious, creative, and diverse. We’re proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Even if you don’t meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria — we don’t want that to be the reason we miss out on great talent.